Triple
T12545109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monica Lewinsky |
E299940
|
entity |
| Predicate | appearedIn |
P795
|
FINISHED |
| Object | TED conference |
E62020
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: TED conference | Statement: [Monica Lewinsky, appearedIn, TED conference]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TED conference Context triple: [Monica Lewinsky, appearedIn, TED conference]
-
A.
TED conferences
chosen
TED conferences are globally renowned events where leading thinkers and innovators deliver short, impactful talks on technology, entertainment, design, and a wide range of other ideas worth spreading.
-
B.
TED
TED is the National Rail station code for Teddington railway station in southwest London, England.
-
C.
TEDx
TEDx is a program of independently organized local events licensed by TED that feature live speakers and recorded TED Talks to share ideas in communities around the world.
-
D.
TED.com
TED.com is the official online platform where TED shares its collection of TED Talks, conferences, and ideas worth spreading with a global audience.
-
E.
TechCrunch
TechCrunch is a leading technology news website and media platform known for its coverage of startups, Silicon Valley, and the tech industry.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6ada707008190aaec1238117c9379 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9547f9a1c81908f54c58a116a8446 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f655801cac8190b1f9a72f8fed0399 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 9:57 p.m.